AutoER: Automated Entity Resolution using Generative Modelling. - Renzhi Wu; Sanya Chaba; Saurabh Sawlani; Xu Chu 002; Saravanan Thirumuruganathan (CoRR, 2019)

Real Time Pattern Matching with Dynamic Normalization. - Renzhi Wu; Sergey Sukhanov; Christian Debes (CoRR, 2019)

GOGGLES: Automatic Image Labeling with Affinity Coding. - Nilaksh Das; Sanya Chaba; Renzhi Wu; Sakshi Gandhi; Duen Horng Chau; Xu Chu 002 (SIGMOD Conference, 2020)

ZeroER: Entity Resolution using Zero Labeled Examples. - Renzhi Wu; Sanya Chaba; Saurabh Sawlani; Xu Chu 002; Saravanan Thirumuruganathan (SIGMOD Conference, 2020)

Nearest Neighbor Classifiers over Incomplete Information: From Certain Answers to Certain Predictions. - Bojan Karlas; Peng Li 062; Renzhi Wu; Nezihe Merve Gürel; Xu Chu 002; Wentao Wu 001; Ce Zhang 001 (Proc. VLDB Endow., 2020)

Dynamic pattern matching with multiple queries on large scale data streams. - Sergey Sukhanov; Renzhi Wu; Christian Debes; Abdelhak M. Zoubir (Signal Process., 2020)

Improving video anomaly detection performance by mining useful data from unseen video frames. - Renzhi Wu; Shuai Li 001; Chenglizhao Chen; Aimin Hao (Neurocomputing, 2021)

Learning to be a Statistician: Learned Estimator for Number of Distinct Values. - Renzhi Wu; Bolin Ding; Xu Chu 002; Zhewei Wei; Xiening Dai; Tao Guan; Jingren Zhou 001 (Proc. VLDB Endow., 2021)

Demonstration of Panda: A Weakly Supervised Entity Matching System. - Renzhi Wu; Prem Sakala; Peng Li 062; Xu Chu 002; Yeye He (Proc. VLDB Endow., 2021)

A Model-Agnostic Approach for Learning with Noisy Labels of Arbitrary Distributions. - Shuang Hao 002; Peng Li 062; Renzhi Wu; Xu Chu 002 (ICDE, 2022)

Learned Label Aggregation for Weak Supervision. - Renzhi Wu; Shen-En Chen; Xu Chu (CoRR, 2022)

A Cluster-then-label Approach for Few-shot Learning with Application to Automatic Image Data Labeling. - Renzhi Wu; Nilaksh Das; Sanya Chaba; Sakshi Gandhi; Duen Horng Chau; Xu Chu 002 (ACM J. Data Inf. Qual., 2022)

Decentralized Personalized Online Federated Learning. - Renzhi Wu; Saayan Mitra; Xiang Chen; Anup B. Rao (IEEE Big Data, 2023)

Learning Hyper Label Model for Programmatic Weak Supervision. - Renzhi Wu; Shen-En Chen; Jieyu Zhang 001; Xu Chu (ICLR, 2023)

Rethinking Similarity Search: Embracing Smarter Mechanisms over Smarter Data. - Renzhi Wu; Jingfan Meng; Jie Jeff Xu; Huayi Wang; Kexin Rong 001 (CoRR, 2023)

Ground Truth Inference for Weakly Supervised Entity Matching. - Renzhi Wu; Alexander Bendeck; Xu Chu 002; Yeye He (Proc. ACM Manag. Data, 2023)

Experiences and Lessons Learned from the SIGMOD Entity Resolution Programming Contests. - Andrea De Angelis; Maurizio Mazzei; Federico Piai; Paolo Merialdo; Giovanni Simonini; Luca Zecchini; Sonia Bergamaschi; Donatella Firmani; Xu Chu 002; Peng Li 062; Renzhi Wu (SIGMOD Rec., 2023)

User-centered Programmatic Data Labeling. - Renzhi Wu (2024)

SketchQL Demonstration: Zero-shot Video Moment Querying with Sketches. - Renzhi Wu; Pramod Chunduri; Dristi J. Shah; Ashmitha Julius Aravind; Ali Payani; Xu Chu 002; Joy Arulraj; Kexin Rong 001 (Proc. VLDB Endow., 2024)

SketchQL: Video Moment Querying with a Visual Query Interface. - Renzhi Wu; Pramod Chunduri; Ali Payani; Xu Chu 002; Joy Arulraj; Kexin Rong 001 (Proc. ACM Manag. Data, 2024)